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Found 7 papers, 3 papers with code
Relation-Aware Pyramid Network (RapNet) for temporal action proposal
In this technical report, we describe our solution to temporal action proposal (task 1) in ActivityNet Challenge 2019.
Layer Pruning for Accelerating Very Deep Neural Networks
In this paper, we propose an adaptive pruning method.
Focusing and Diffusion: Bidirectional Attentive Graph Convolutional Networks for Skeleton-based Action Recognition
A collection of approaches based on graph convolutional networks have proven success in skeleton-based action recognition by exploring neighborhood information and dense dependencies between intra-frame joints.
Ranked #36 on
Skeleton Based Action Recognition
on NTU RGB+D
Accurate Temporal Action Proposal Generation with Relation-Aware Pyramid Network
Accurate temporal action proposals play an important role in detecting actions from untrimmed videos.
Relation-aware Video Reading Comprehension for Temporal Language Grounding
Temporal language grounding in videos aims to localize the temporal span relevant to the given query sentence.
You Need to Read Again: Multi-granularity Perception Network for Moment Retrieval in Videos
Moment retrieval in videos is a challenging task that aims to retrieve the most relevant video moment in an untrimmed video given a sentence description.
Boundary-Denoising for Video Activity Localization
To alleviate the boundary ambiguity, we propose to study the video activity localization problem from a denoising perspective.
Ranked #1 on
Video Grounding
on MAD
